Variable selection under multiple imputation using the bootstrap in a prognostic study期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

按检索

Variable selection under multiple imputation using the bootstrap in a prognostic study

Authors:	Martijn W Heymans Dirk L Knol Willem van Mechelen Henrica CW de Vet

Institution:	(1) Department of Methodology and Applied Biostatistics, Vrije Universiteit, Institute for Health Sciences, Amsterdam, The Netherlands;(2) Body@Work, Research Center Physical Activity, Work and Health, TNO-VUmc, Amsterdam, The Netherlands;(3) Department of Public and Occupational health, VU University Medical Center, Amsterdam, The Netherlands;(4) Institute for Research in Extramural Medicine, VU University Medical Center, Amsterdam, The Netherlands;(5) TNO Quality of Life, Leiden, The Netherlands;(6) Department of Methodology and Statistics, University of Utrecht, Amsterdam, The Netherlands;(7) Clinical Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands;(8) EMGO-Institute (Metropolitan building), VU University Medical Center, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands

Abstract:	Background Missing data is a challenging problem in many prognostic studies. Multiple imputation (MI) accounts for imputation uncertainty that allows for adequate statistical testing. We developed and tested a methodology combining MI with bootstrapping techniques for studying prognostic variable selection.

Keywords:
本文献已被 SpringerLink 等数据库收录！